Plenary Lecture

Non-Stationary Dynamics in Reliability Analysis of Adaptive Multi-Agent Systems

Associate Professor Gabriela Tont
Control Systems Engineering and Management Department
Faculty of Electrical Engineering and Information Technology
University of Oradea

Abstract: In uncertain dynamic business environments, the decisions that profile the direction of the organization in the near future have to meet factors that influence organization's operating situation with the external influences.
Allocating the resources of complex systems between different alternatives and over different time periods in an uncertain environment (clients, suppliers, competition, technology; laws, market, social and economic trends) in cost constrain conditions are important aspects that technical and economic agents have to evaluate in decision process. The cost, time, and resource savings decisions are based on decision making model that conclude which decisions need to be made and how to find alternatives for each decision in the benefit the company. Modeling reliability by means of artificial intelligence is increasingly required because of multiple problems that systems are facing in socio-technical, and economical context. The risk prediction and decision making tools are designed by means of interconnected structures. The risk estimation is aligning in the larger framework of solving business and technical issues by adopting solution and decision-making under the simultaneous multi-objective conditions where processes are mainly non-stationary.
A process is stationary when the statistical properties as joint probability distribution, and consequently mean and variance (if they appear) are invariant. Allowing that stationarity is an unrealistic assumption for the multi-state components of complex systems where row data are not seasonal, the numerical characteristics of the non-stationary of complex structure are developed in the paper. Considering the uncertainty of transitions states, the paper proposes a stochastic model of assessing probability transition states, applying the, non-homogeneous Markov chain in an ageing system. The capability of time-dependent method to describe a multi-state system is based on a case study, assessing the operational situation of complex system. The rationality and validity of the presented model are demonstrated via an engineering example. The effect of randomness of the structural parameters is also examined.

Brief Biography of the Speaker: Graduated “Politehnica” Institute of Bucharest and defined her professional training by earning Ph. D degree in Electrical Engineering at Technical University Cluj Napoca.
Actively caring out research and teaching projects in reliability engineering and management is, at present, associate professor of the Faculty of Electrical Engineering and Information Technology, University of Oradea.
Recent research conducted includes reliability analysis and data modeling in dynamical, non-linear systems, simulation modeling for risk assessment in context-aware computing and intelligent e-learning technologies.
Certified external quality auditor, has an extensive experience in strategic total quality management applied in manufacturing processes and quality system improvements with six sigma initiatives, optimizing TQM (zero defects, six sigma), quality planning (QFD).
Participated in several international and national projects as director, scientific manager or member.
In the fields above she has authored and/or co-authored 10 books and 9 chapters in books, 31 papers in editor conference proceedings; 67 journal papers, 106 conference papers.
Member in Editorial Boards of 7 journals, delivered 17 plenary/keynote lectures.
Reviewer for WSEAS conferences WSEAS Transactions journals.
Actively participated at international and national conferences, in 16 was a member of scientific and/or organizing committees of conferences.

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